ASF GitHub Bot commented on FLINK-9664:

walterddr commented on a change in pull request #6425: [FLINK-9664][Doc] fixing 
documentation in ML quick start
URL: https://github.com/apache/flink/pull/6425#discussion_r209430609

 File path: docs/dev/libs/ml/quickstart.md
 @@ -129,6 +129,10 @@ and the [test set 
 This is an astroparticle binary classification dataset, used by Hsu et al. 
[[3]](#hsu) in their
 practical Support Vector Machine (SVM) guide. It contains 4 numerical 
features, and the class label.
+Before importing the traning and test dataset, Flink SVM only supports 
threshold binary values of 
+`+1.0` and `-1.0`. Thus a conversion is needed upon downloading the svmguide1 
dataset since it is 
+labelled using `1`s and `0`s.
 Review comment:
   thx for the detail explanation @azagrebin . Sorry for the previous 
confusion. I updated the document, please take another look when you have time 

This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:

> FlinkML Quickstart Loading Data section example doesn't work as described
> -------------------------------------------------------------------------
>                 Key: FLINK-9664
>                 URL: https://issues.apache.org/jira/browse/FLINK-9664
>             Project: Flink
>          Issue Type: Bug
>          Components: Documentation, Machine Learning Library
>    Affects Versions: 1.5.0
>            Reporter: Mano Swerts
>            Assignee: Rong Rong
>            Priority: Major
>              Labels: documentation-update, machine_learning, ml, 
> pull-request-available
>   Original Estimate: 1h
>  Remaining Estimate: 1h
> The ML documentation example isn't complete: 
> [https://ci.apache.org/projects/flink/flink-docs-release-1.5/dev/libs/ml/quickstart.html#loading-data]
> The referred section loads data from an astroparticle binary classification 
> dataset to showcase SVM. The dataset uses 0 and 1 as labels, which doesn't 
> produce correct results. The SVM predictor expects -1 and 1 labels to 
> correctly predict the label. The documentation, however, doesn't mention 
> that. The example therefore doesn't work without a clue why.
> The documentation should be updated with an explicit mention to -1 and 1 
> labels and a mapping function that shows the conversion of the labels.

This message was sent by Atlassian JIRA

Reply via email to